“The climate scientists at the centre of a media storm over leaked emails were yesterday cleared of accusations that they fudged their results and silenced critics, but a review found they had failed to be open enough about their work.”
- Keep yourself organized – be able to find your files (data inputs, analytic scripts, outputs at various stages of the analytic process, etc.)
- Track your science processes for reproducibility – be able to match up your outputs with exact inputs and transformations that produced them
- Better control versions of data – easily identify versions that can be periodically purged
- To avoid data loss (e.g. making backups)
- Format your data for re-use (by yourself or others)
- Be prepared: Document your data for your own recollection, accountability, and re-use (by yourself or others)
- Gain credibility and recognition for your science efforts through data sharing!
The data life cycle provides a high level overview of the stages involved in successful management and preservation of data for use and reuse.
Courtesy of DataONE
A data managment plan describes how you will manage your data during a reserach project.
For any scientific project, it is good practice to prepare a data management plan (DMP). The process of creating your DMP will force you to think about potential issues realted to the project’s data that could affect timeline, costs and personel needed.
- It might be required by founding agency
- It will help you in your project planning and ressources allocations
- It will help you to share and promote your work (Publications, Data citation, …)
Accidents happen !!!